Were you one of the 300+ lucky practitioners, data analysts, statisticians, improvement advisers, program managers, engineers, clinical directors, coordinators and quality professionals who attended the 2019 Minitab Insights Global Conference this past fall?
Don’t worry if you were unable to join — with the help of our expert Jenn Atlas, we’ve rounded up
the 5 Key Challenges and Learnings you need to know.
1. Machine Learning Methods are Important Components of the Modern Problem-Solver's Portfolio
Machine learning, defined as algorithms and statistical models that computer systems use to perform a specific task using patterns and inference rather than explicit instructions, has been around for years, but has recently been gaining in popularity and use due to the sheer volume of data that is now available thanks to digitization.
With more data readily accessible, using original problem-solving methods may no longer be the fastest or most efficient ways for practitioners to solve their problems. This is where machine learning methods are the most helpful as they are better built to handle larger quantities of data and still ultimately provide accurate answers quickly to the problems that need to be solved.
2. Small Data Still Matters
We've mentioned that more data exists than ever before but that brings us to our next point: just because you can obtain and analyze more data, doesn't mean you should. Remember that there are still plenty of scenarios where it's better to work with smaller amounts of quality data and be more thoughtful with the analysis rather than modeling and analyzing huge sets of data with no specific purpose.
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3. Measurement System Analysis is Always a Critical First Step
Although measurement system analysis may not seem overly exciting, many of the sessions during 2019 Minitab Insights highlighted its importance because without proper verification it's hard to prove the validity of any experiment, measurement or findings.
4. Operations Excellence in Healthcare is Steadily Growing
There is a tremendous opportunity to improve patient experience in the Healthcare Services sector.
Healthcare at a high level may seem to have similar problems at times to those in manufacturing, but there are two main differences between these industries:
- Healthcare often has to deal more with politics, process and people (in the form of patients) so the margin for error is much slimmer since lives could be on the line.
- Healthcare professionals can have different skill sets and ways of thinking than a manufacturing professional. These professionals are generally more process-oriented, have more people skills and less background in analytics, therefore their training and application of improvement methods could be unique and unlike their manufacturing counterparts.
5. Structured Problem-Solving Will Never Go Out of Style
Countless speakers, including our plenary John Aarons, brought attention to the fact that time and time again problem-solving teams really do benefit from following structured methodology like CRISP-DM, DMAIC, DMADV and SEMMA.
These methods showcase the thought and intention behind solving a particular problem and often still are a strategic way to get buy-in from leadership and other stakeholders within an organization.
Get a deeper dive on these topics and more plus the opportunity to be among the brightest minds in quality, improvement and data analysis and share your knowledge and experience with other industry leaders at the 2020 Minitab Insights Global Conference! The dates and location were just announced, so we hope to see you there!